Enhanced wireless node location using differential signal strength metric

ABSTRACT

A wireless node location mechanism that employs a differential signal strength metric to reduce the errors caused by variations in wireless node transmit power, errors in signal strength detection, and/or direction-dependent path loss. As opposed to using the absolute signal strength or power of an RF signal transmitted by a wireless node, implementations of the location mechanism compare the differences between signal strength values detected at various pairs of radio receivers to corresponding differences characterized in a model of the RF environment. One implementation searches for the locations in the model between each pair of radio receivers where their signal strength is different by an observed amount.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application makes reference to the following commonly owned U.S.patent applications and/or patents, which are incorporated herein byreference in their entirety for all purposes:

U.S. patent application Ser. No. 10/155,938 in the name of Patrice R.Calhoun, Robert B. O'Hara, Jr. and Robert J. Friday, entitled “Methodand System for Hierarchical Processing of Protocol Information in aWireless LAN;”

U.S. patent application Ser. No. 10/183,704 in the name of Robert J.Friday, Patrice R. Calhoun, Robert B. O'Hara, Jr., Alexander H. Hillsand Paul F. Dietrich, and entitled “Method and System for DynamicallyAssigning Channels Across Multiple Radios in a Wireless LAN;”

U.S. patent application Ser. No. 10/407,357 in the name of Patrice R.Calhoun, Robert B. O'Hara, Jr. and Robert J. Friday, entitled “Methodand System for Hierarchical Processing of Protocol Information in aWireless LAN;”

U.S. patent application Ser. No. 10/407,370 in the name of Patrice R.Calhoun, Robert B. O'Hara, Jr. and David A. Frascone, entitled “WirelessNetwork System Including Integrated Rogue Access Point Detection;” and

U.S. patent application Ser. No. 10/447,735 in the name of Robert B.O'Hara, Jr., Robert J. Friday, Patrice R. Calhoun, and Paul F. Dietrichand entitled “Wireless Network Infrastructure including WirelessDiscovery and Communication Mechanism;” and

U.S. patent application Ser. No. 10/788,645 in the name of Robert J.Friday and Alexander H. Hills, entitled “Selective Termination ofWireless Connections to Refresh Signal Information in Wireless NodeLocation Infrastructure;”

U.S. patent application Ser. No. 10/802,366 in the name of Paul F.Dietrich, Gregg Scott Davi and Robert J. Friday, entitled “Location ofWireless Nodes Using Signal Strength Weighting Metric;” and

U.S. patent application Ser. No. 10/848,276 in the name of Paul F.Dietrich, Gregg Scott Davi and Robert J. Friday, entitled “Wireless NodeLocation Mechanism Featuring Definition of Search Region to OptimizeLocation Computation.”

FIELD OF THE INVENTION

The present invention relates to estimating the location of wirelessnodes in wireless network environments and, more particularly, to adifferential signal strength metric directed to improving the accuracyof wireless node location mechanisms.

BACKGROUND OF THE INVENTION

Market adoption of wireless LAN (WLAN) technology has exploded, as usersfrom a wide range of backgrounds and vertical industries have broughtthis technology into their homes, offices, and increasingly into thepublic air space. This inflection point has highlighted not only thelimitations of earlier-generation systems, but the changing role WLANtechnology now plays in people's work and lifestyles, across the globe.Indeed, WLANs are rapidly changing from convenience networks tobusiness-critical networks. Increasingly users are depending on WLANs toimprove the timeliness and productivity of their communications andapplications, and in doing so, require greater visibility, security,management, and performance from their network.

The rapid proliferation of lightweight, portable computing devices andhigh-speed WLANs enables users to remain connected to various networkresources, while roaming throughout a building or other physicallocation. The mobility afforded by WLANs has generated a lot of interestin applications and services that are a function of a mobile user'sphysical location. Examples of such applications include: printing adocument on the nearest printer, locating a mobile user or rogue accesspoint, displaying a map of the immediate surroundings, and guiding auser inside a building. The required or desired granularity of locationinformation varies from one application to another. Indeed, the accuracyrequired by an application that selects the nearest network printer, orlocates a rogue access point, often requires the ability to determine inwhat room a wireless node is located. Accordingly, much effort has beendedicated to improving the accuracy of wireless node locationmechanisms.

The use of radio signals to estimate the location of a wireless deviceor node is known. For example, a Global Positioning System (GPS)receiver obtains location information by triangulating its positionrelative to four satellites that transmit radio signals. The GPSreceiver estimates the distance between each satellite based on the timeit takes for the radio signals to travel from the satellite to thereceiver. Signal propagation time is assessed by determining the timeshift required to synchronize the pseudo-random signal transmitted bythe satellite and the signal received at the GPS receiver. Althoughtriangulation only requires distance measurements from three points, anadditional distance measurement from a fourth satellite is used forerror correction.

The distance between a wireless transmitter and a receiver can also beestimated based on the strength of the received signal, or moreaccurately the observed attenuation of the radio signal. Signalattenuation refers to the weakening of a signal over its path of traveldue to various factors like terrain, obstructions and environmentalconditions. Generally speaking, the magnitude or power of a radio signalweakens as it travels from its source. The attenuation undergone by anelectromagnetic wave in transit between a transmitter and a receiver isreferred to as path loss. Path loss may be due to many effects such asfree-space loss, refraction, reflection, and absorption.

In business enterprise environments, most location-tracking systems arebased on RF triangulation or RF fingerprinting techniques. RFtriangulation calculates a mobile user's location based upon thedetected signal strength of nearby access points (APs). It naturallyassumes that signal strength is a factor of proximity, which is true amajority of the time. However, the multipath phenomenon encountered inindoor RF environments does present certain difficulties in locatingwireless nodes, since reflection and absorption of RF signals affectsthe correlation between signal strength and proximity. RF fingerprintingcompares a mobile station's view of the network infrastructure (i.e.,the strength of signals transmitted by infrastructure access points)with a database that contains an RF physical model of the coverage area.This database is typically populated by either an extensive site surveyor an RF prediction model of the coverage area. For example, Bahl etal., “A Software System for Locating Mobile Users: Design, Evaluation,and Lessons,” http://research.microsoft.com/˜bahl/Papers/Pdf/radar.pdf,describes an RF location system (the RADAR system) in a WLANenvironment, that allows a mobile station to track its own locationrelative to access points in a WLAN environment.

The RADAR system relies on a so-called Radio Map, which is a database oflocations in a building and the signal strength of the beacon packetsemanating from the access points as observed, or estimated, at thoselocations. For example, an entry in the Radio Map may look like (x, y,z, ss_(i) (i=1 . . . n)), where (x, y, z) are the physical coordinatesof the location where the signal is recorded, and ss_(i) is the signalstrength of the beacon signal emanating from the ith access point.According to Bahl et al., Radio Maps may be empirically created based onheuristic evaluations of the signals transmitted by the infrastructureradios at various locations, or mathematically created using amathematical model of indoor RF signal propagation. To locate theposition of the mobile user in real-time, the mobile station measuresthe signal strength of each of access points within range. It thensearches a Radio Map database against the detected signal strengths tofind the location with the best match. Bahl et al. also describeaveraging the detected signal strength samples, and using a trackinghistory-based algorithm, to improve the accuracy of the locationestimate. Bahl et al. also address fluctuations in RF signal propagationby using multiple Radio Maps and choosing the Radio Map which bestreflects the current RF environment. Specifically, one access pointdetects beacon packets from other access points and consults a radio mapto estimate its location, and evaluates the estimated location with theknown location. The RADAR system chooses the Radio Map which bestcharacterizes the current RF environment, based on a sliding windowaverage of received signal strengths.

While the RADAR system works for its intended objective, even in thissystem, location accuracy decreases with the error in detecting thestrength of RF signals. For example, individual differences as to howtwo different wireless nodes detect and report signal strength can causeerrors in location, since the Radio Maps assume no error in suchmeasurements. Accordingly, two wireless nodes in the same location thatdetect different signal strengths will compute different estimatedlocations. Still further, while the RADAR system allows a mobile stationto track its own location, it does not disclose a system that allows theWLAN infrastructure to track the location of wireless nodes, such asrogue access points. Such a system is desirable as it obviates the needfor special client software to be installed on the mobile stations.

This paradigm shift, however, presents certain problems. As discussedabove, the Radio Maps in the RADAR system are constructed from the pointof view of a wireless node in an RF environment that includes accesspoints in known locations. In other words, the Radio Maps areconstructed based on heuristic and/or mathematical evaluations of thepropagation of signals from the access points to a wireless node at agiven location. Accordingly, the RADAR system need not assume symmetryof path loss between a given location and the access points in the RADARsystem, since the mobile station detects the signal strength of theaccess points and computes its own location. In addition, since thelocation of a wireless node is based on path loss, the transmit power ofthe radio transmitters used to determine location must also be known. Inthe RADAR system, this is not problematic, since the signals used todetermine location are transmitted by access points, whose transmitpower can be controlled or easily determined. Estimating location basedon signals transmitted by a wireless node, however, can be problematic,since transmit power can vary among wireless device manufacturers,and/or may be individually configured by the mobile user. Furthermore,the more complicated issue of variable transmit power exists not onlydue to the device or intended application itself, but also due toplacement of the wireless node (e.g., a RFID tag, etc.) placed among orinside of other objects, or located within or behind various physicalbarriers or obstructions.

One approach to this problem is to assume symmetry in path loss betweena given location in an RF environment and the radio transceivers used todetect signals transmitted by the wireless nodes. Furthermore, theseapproaches also assume a uniform transmit power for the wireless nodesin light of the fact that legal regulations, as well as current chip settechnology, generally places an upper limit on transmit power. These twoassumptions, however, can significantly impact the accuracy of locatinga wireless node. As discussed above, the RADAR system, for example,finds the location coordinates in the Radio Map that are the best fitbased on the detected signal strengths. That is, for each point in theRadio Map, the location metric computes the Euclidean distance betweenthe detected signal strength values and the values in the Radio Map.

The following equation provides an illustrative example, assume fordidactic purposes that a given wireless node is detected by three accesspoints. The signal strength samples are RSSIap1 RSSIap2, and RSSIap3,while the RF coverage maps for each of the access points are denoted asMAPap1, MAPap2, MAPap3, where the coverage maps include access pointsignal strength values detected or computed for different locations in adefined region. Again, assuming path loss symmetry and a uniformtransmit power, individual error surfaces for each access point can becreated based on the signal strength detected at each access point,(RSSIap1, etc.) and the signal strength values in the individualcoverage maps (e.g., MAPap1, etc.). That is, the error surface is thedifference between the observed signal strength at a given access pointless the signal strength values in the coverage map. The locations inthis coverage map where the difference is zero are the most likelylocations. In many situations, however, the measured signal strengths,RSSIap1 RSSIap2, and RSSIap3, do not match the signal strengths recordedin the coverage maps MAPap1, MAPap2, MAPap3 at any one location. In thiscase, it is desirable to find the location that is “closest” to matchingRSSIap1 RSSIap2, and RSSIap3—in other words, the location that minimizessome function of MAPap1, MAPap2, MAPap3, RSSIap1 RSSIap2, and RSSIap3.Bahl et al., supra, describe several ways in which this function iscreated, including minimum mean squared error, minimum distance, andminimum Manhattan grid distance. Furthermore, a total error surface,ErrSurf, can be computed based on the sum of the squares (to neutralizepositive and negative differences) of the individual error surfaces(i.e., the difference between the detected signal strength values andthe signal strength values in each coverage maps), as follows:ErrSurf=[(RSSIap1−MAPap1)^2+(RSSIap2−MAPap2)^2+(RSSIap3−MAPap3)^2]/3In one implementation, the estimated wireless node location is derivedfrom the minimum or minimum of this total error surface.

However, a change in the wireless node's effective transmit power (or,in the RADAR system, inaccuracies in detecting signal strength by thewireless nodes) will adversely affect the accuracy of this metric. Forexample, an N dB difference between the actual and assumed transmitpower of a wireless node would cause a N dB change in the detectedsignal strengths. Rather than merely shifting the individual signalstrength differences for each point in the individual error surfaces upby some fixed amount, the individual differences between the detectedsignal strengths and the signal strength values in the error surface canchange quite dramatically. Indeed, each point in the individual errorsurfaces are shifted an amount proportional to the dB error. Thiscircumstance moves some areas of the total error surface up relative toothers, and some areas of the total error surface down relative toothers, significantly altering the shape of the error surface, as wellas the location, shape, and size of its minima. It also createsunpredictable error with changes in transmit power. Similar problemswill occur for a fixed error in the “link or path loss symmetry” wherethe path loss from access point to wireless node differs from the pathloss from wireless node to access point by some fixed amount due topropagation characteristics, vantage point, and the like. In addition,sources of RF interference typically have unknown transmit powers, andmay only partially overlap the frequency band in which wireless nodesoperate. Estimating the location of these interference sources requiresa method that does not depend entirely on the absolute detected signalstrength value.

In light of the foregoing, a need in the art exists for a wireless nodelocation mechanism that reduces the errors in computing the location ofa wireless node due to commonly occurring circumstances, such asvariations in wireless node transmit power, errors in signal strengthdetection, and/or direction-dependent path loss. Embodiments of thepresent invention substantially fulfill this need.

SUMMARY OF THE INVENTION

The present invention provides a wireless node location mechanism thatemploys a differential signal strength metric to reduce the errorscaused by variations in wireless node transmit power, errors in signalstrength detection, and/or direction-dependent path loss. As opposed tousing the absolute signal strength or power of an RF signal transmittedby a wireless node, implementations of the present invention compare thedifferences between signal strength values detected at various pairs ofradio receivers to corresponding differences characterized in a model ofthe RF environment. One implementation of the invention searches for thelocations in the model between each pair of radio receivers where theirsignal strength is different by an observed amount. In otherimplementations, the differential signal strength metric can be used asone component of a wireless node location mechanism that also usesabsolute signal strength values. As discussed in more detail below, thewireless node location mechanism can be incorporated into wirelessnetwork environments, such as 802.11 networks, to estimate the locationof mobile stations, rogue access points and other wireless nodes.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram including a wireless node locationmechanism according to an implementation of the present invention.

FIG. 2 is a flow chart diagram illustrating the overall process flowdirected to the location of a wireless node according to animplementation of the present invention.

FIG. 3 is a functional block diagram illustrating a wireless networksystem according to an implementation of the present invention.

FIG. 4 is a functional block diagram showing the wireless node locationfunctionality of a central control element in the wireless networksystem of FIG. 3.

FIG. 5 is a flow chart diagram illustrating the overall process flowdirected to estimating the location of a wireless node using acombination of the differential signal strength methodology and anabsolute signal strength methodology.

DESCRIPTION OF PREFERRED EMBODIMENTS

A. Wireless Node Location and Differential Signal Strength Metric

FIG. 1 illustrates the basic operating components of the wireless nodelocation mechanism according to an implementation of the presentinvention. As FIG. 1 shows, the wireless node location mechanismincludes a wireless node location module 59 and a plurality ofinfrastructure radio transceivers 58 disposed throughout a physicalspace. One skilled in the art will recognize that the system depicted inFIG. 1 represents an example of the basic components of the inventionand is mostly for didactic purposes. As discussed more fully below, thefunctionality generally denoted by infrastructure radio transceivers 58and wireless node location module 59 can be integrated into a variety ofsystems, such as wireless systems dedicated for location of wirelessnodes, or WLAN or other wireless network systems.

Infrastructure radio transceivers 58 generally comprise at least oneantenna, a radio transmit/receive unit, and control logic (e.g., a802.11 control unit) to control the transmission and reception of radiosignals according to a wireless communications protocol. Infrastructureradio transceivers 58, in one implementation, are disposed in knownand/or fixed locations throughout a physical space, such as a room, acollection of rooms, a floor of a building, an entire building, or anarbitrarily-defined region, including outside environments, over whichinfrastructure radio transceivers 58 provide RF coverage.

A.1. Infrastructure Radio Transceiver

Infrastructure radio transceivers 58 are operative to detect thestrength of received radio-frequency signals, such as the signals 57transmitted by wireless node 56 and by other radio transceivers, andprovide the detected signal strength data for corresponding wirelessnodes to wireless node location module 59. In one implementation,infrastructure radio transceivers 58 are also operative to transmit andreceive wireless or radio-frequency signals according to a wirelesscommunications protocol, such as the IEEE 802.11 WLAN protocol.Infrastructure radio transceivers 58, in one implementation, can operateon a selected channel from a plurality of channels in a given band. Inanother implementation, infrastructure radio transceivers 58 can alsooperate in more than one band. For example, infrastructure radioreceivers 58 may be configured to operate in either the 802.11a-5 GHzband, and/or the 802.11b/g-2.4 GHz band. In one implementation,infrastructure radio transceivers 58 can be configured to collect thesignal strength information associated with wireless nodes and transmitthe collected data in response to SNMP or other requests by wirelessnode location module 59. In other implementations, the infrastructureradio transceivers 58 can transmit signal strength information on aregular or periodic basis. As discussed below, other methods forcollecting signal strength data may also be employed.

Identification of wireless nodes depends on the wireless communicationsprotocol in use. For 802.11 WLAN environments, for example, wirelessnodes can be identified based on MAC address. Furthermore, wirelessnodes can be authorized mobile stations, such as remote client elements16, 18 (see FIG. 3), rogue systems (e.g., rogue access points and/orrogue mobile stations), as well as authorized access points for which nolocation information is known. In other implementations, wireless nodescan be identified based on a unique property of the RF signal, such as agiven frequency channel, or a unique signal pattern, and the like. Forexample, the wireless node location functionality may be employed tolocate a detected source of interference, such as a non-802.11 compliantdevice.

In one implementation, infrastructure radio transceivers 58 are alsooperable to communicate with one or more mobile stations, such aswireless node 56, according to a wireless communication protocol. Forexample, radio transceiver 58, in one implementation, is an access pointor other WLAN component. In one implementation, radio transceiver 58 isoperably connected to a Local Area Network (LAN), Wide Area Network(WAN) or other wireline network to bridge traffic between mobilestations and the wireline network. As discussed more fully below, radiotransceiver 58 may also be an access element or light weight accesspoint in a wireless network featuring hierarchical processing ofprotocol information. In one implementation, the radio transceiver 58implements the 802.11 protocols (where 802.11, as used herein,generically refers to the IEEE 802.11 standard for wireless LANs and allits amendments). Of course, the present invention can be used inconnection with any suitable radio-frequency-based wireless network orcommunications protocol.

In one implementation, infrastructure radio transceivers 58 make use ofthe signal strength detection functionality residing on a wirelessnetwork interface adapter to detect signal strength on a frame-by-framebasis. For example, the IEEE 802.11 standard defines a mechanism bywhich RF energy is measured by the circuitry (e.g., chip set) on awireless network adapter or interface card. The IEEE 802.11 protocolspecifies an optional parameter, the receive signal strength indicator(RSSI). This parameter is a measure by the PHY layer of the energyobserved at the antenna used to receive the current packet or frame.RSSI is measured between the beginning of the start frame delimiter(SFD) and the end of the PLCP header error check (HEC). This numericvalue is an integer with an allowable range of 0-255 (a 1-byte value).Typically, 802.11 chip set vendors have chosen not to actually measure256 different signal levels. Accordingly, each vendor's 802.11-compliantadapter has a specific maximum RSSI value (“RSSI_Max”). Therefore, theRF energy level reported by a particular vendor's wireless networkadapter will range between 0 and RSSI_Max. Resolving a given RSSI valuereported by a given vendor's chip set to an actual power value (dBm) canbe accomplished by reference to a conversion table. In addition, somewireless networking chip sets actually report received signal strengthin dBm units, rather than or in addition to RSSI. Other attributes ofthe signal can also be used in combination with received signal strengthor as an alternative. For example, the detected Signal-to-Noise Ratio(SNR) during packet reception can be used in determining overlay signaltransmit power. Again, many chip sets include functionality andcorresponding APIs to allow for a determination of SNRs associated withpackets received from other transceivers 58 and/or wireless node 56. Theresulting signal strength information, in one implementation, can beassociated with a time stamp corresponding to the receipt of the frame.As discussed herein, this signal strength information can be collectedat each infrastructure radio transceiver 58 and/or the wireless nodelocation module 59 in suitable data structures.

A.2. Wireless Node Location Module

Wireless node location module 59, in one implementation, collects signalstrength data received from infrastructure radio transceivers 58 andmaintains the signal strength data in association with a wireless nodeidentifier, and an identifier for the infrastructure radio transceiver58 which provided the signal strength data. Wireless node locationmodule 59, in one implementation, is also configured to distinguishbetween signals received from infrastructure radio transceivers 58 andsignals received from other wireless nodes based on the wireless nodeidentifier. In one implementation, wireless node location module 59maintains a variety of data structures for storing signal strengthinformation. For example, one data structure is used to store the signalstrength of signals transmitted between infrastructure radiotransceivers 58. In one implementation, wireless node location module 59stores this signal strength data in a N×N IRT matrix, where N is thenumber of infrastructure radio transceivers 58. The column entries cancorrespond to the transmitting transceiver, while the row entriescorrespond to the receiving transceiver, or vice versa. Various entriesin this matrix may be null values as all infrastructure radiotransceivers may not, and in most deployments probably will not, be ableto detect one another. Wireless node location module 59, in oneimplementation, maintains signal strength data for all other wirelessnodes in tables or other suitable data structures. In oneimplementation, wireless node location module 59 maintains, for eachradio transceiver 58, a separate table including at least two fields: 1)a wireless node identifier; and 2) the detected signal strength.Additional fields may also include a time stamp indicating the time theinfrastructure radio transceiver 58 received the signal. In oneimplementation, when the memory space allocated to the wireless nodetables is depleted, the least recently used/updated entry as indicatedby the time stamps is overwritten. In one implementation, wireless nodelocation module 59 filters the signal strength data received from theinfrastructure radio transceivers 58 against a list of wireless nodeidentifiers in order to identify the appropriate data structure toupdate. One skilled in the art will recognize that a variety of datastructures beyond matrixes and tables can be used.

As discussed above, signal strengths are detected, in oneimplementation, on a frame-by-frame basis. Accordingly, in oneembodiment, the signal strength data maintained by wireless nodelocation module 59 can be updated as the frames/packets are received. Inone implementation, the latest signal strength value is used toessentially overwrite the old value. In other implementations, however,an average, moving average or weighted moving average can be used ifsuccessive wireless frames corresponding to a given wireless node areencountered within a threshold time interval (e.g., typically resultingfrom a data stream transmission). In such a situation, the time stampcan correspond to the time of the last packet or frame. In addition,while radio transceivers 58 when operating as access points typicallyoperate on different channels, mobile stations at various times (e.g.,transmitting probe requests to find access points) transmit wirelessframes on all available operating channels. This helps to ensure that aplurality of infrastructure radio transceivers 58 detect the mobilestation. In some implementations, one or more infrastructure radiotransceivers 58 that are adjacent to a radio transceiver 58 thatdetected a given wireless node may be directed to switch to a givenoperating channel to listen for signals transmitted by the mobilestation. Still further, as discussed below, the infrastructure radiotransceivers 58 may be commanded to specifically transmit frames on agiven channel for the purpose of updating the signal strength datamaintained by wireless node location module 59. In yet anotherembodiment, the infrastructure radio transceiver 58 or other accesspoint with which a given mobile station is associated may be commandedto disassociate the mobile station. This causes the mobile station totransmit probe requests on all available operating channels, refreshingthe signal strength data collected by neighboring infrastructure radiotransceivers. U.S. patent application Ser. No. 10/788,645 discloses theselective termination of wireless clients to refresh signal strengthinformation in RF location systems.

Wireless node location module 59 also maintains a RF physical model ofthe coverage area associated with the RF environment. As discussed inmore detail below, the RF physical model returns an estimated physicallocation of a wireless node, given the strength of signals detected bythe infrastructure radio transceivers 58, as well as an indication ofthe infrastructure radio transceivers reporting the signal strengths. Inone implementation, the RF physical model characterizes for eachinfrastructure radio transceiver 58 the received signal strengthassociated with a wireless transmitter at a given location. For example,in one implementation, the RF physical model comprises, for eachantenna, a radio coverage map or matrix that indicates the expectedsignal strength detected at an infrastructure radio transceiver andreceived from a wireless node, assuming a uniform transmit power, at agiven location defined in x-, and y-coordinates. This database can bepopulated in a variety of ways. For example, the radio coverage maps canbe populated with the results of an extensive site survey, according towhich a wireless transmitter is placed at different locations in thephysical space. During the site survey, the infrastructure radiotransceivers 58 operate in a listening mode that cycles between theantennas and report the resulting signal strength of the signaltransmitted by the wireless node used to conduct the site survey. In oneimplementation, the infrastructure radio transceivers 58 can beconfigured to transmit the signal strength data back to the wirelesstransmitter, which may be a laptop computer or other wireless device.The coverage maps are constructed by associating the signal strength andlocation data in the coverage maps corresponding to each infrastructureradio transceiver. The coverage maps may also be constructed by having aWLAN tester (or other wireless node) simply measure the signal strengthof frames transmitted by the infrastructure radio transceivers 58 (e.g.,beacon packets) at desired locations within the deployment region. Ifpath loss symmetry is assumed, these values can be used to construct thecoverage maps for each of the infrastructure radio transceivers. Toestimate the location of the wireless node, wireless node locationmodule 59 determines the location coordinates, or range of locationcoordinates, that best fit the coverage maps associated with theinfrastructure radio transceivers 58 selected to locate the wirelessnode based on the detected signal strength data, as discussed in moredetail below.

In one implementation, a coverage map, for each infrastructure radiotransceiver 58, is maintained that includes the signal strengths in anN×M matrix, where N is the number of x-coordinates in the coverage map,and M is the number of y-coordinates in the coverage map. In oneimplementation, the extent of the physical space model by the coveragemaps for each infrastructure radio transceiver 58 are co-extensive. Thecoverage maps for all infrastructure radio transceivers 58 can beco-extensive with the physical space in which the location system isdeployed, or with a boundary configured by a network administrator. Inone implementation, however, knowledge of various antenna attributesassociated with each infrastructure radio transceiver 58—such as antennatype (e.g., omni-directional, directional), peak gain orientation,beamwidth, front-to-back isolation—can be used to compress or reduce thesize of the coverage maps. In one implementation, the coverage maps canbe configured to be substantially coextensive with the antenna patternof each antenna connected to the infrastructure radio transceivers 58out to a threshold signal strength or gain level. For example, thecoverage map for a given antenna can be compressed to the front orintended coverage area of the directional antenna. Of course, other datastructures can be used such as a table including location coordinatesstored in association with tuples of signal strengths and infrastructureradio transceiver antenna identifiers. In addition, if the coverage mapsare compressed, the search for the best fit across selected coveragemaps can be isolated to the overlap between coverage maps associatedwith the antennas selected to locate the wireless node.

In another implementation, the coverage maps of the RF physical modelmay be constructed using an RF prediction model of the coverage area,using mathematical techniques like ray-tracing, and the like. In oneimplementation, the RF prediction model can be computed for eachcoordinate location in a desired physical space, assuming a uniformwireless node transmit power. The estimated signal strength informationfor each infrastructure radio transceiver 58 can be used to populate thecoverage maps discussed above. In an alternative embodiment, RFprediction models can be computed relative to each infrastructure radiotransceiver antenna. Since the present invention allows path losssymmetry and transmit power symmetry between the wireless nodes and theinfrastructure radio transceivers 58 to be assumed, the coverage mapsfor each infrastructure radio transceiver antenna can be populated byusing the computed values at each of the coordinate locations in thecoverage map. Of course, site survey data can also be used to adjust oneor more parameters associated with the RF prediction model used toestimate expected signal strength at the various locations. As above,the boundaries of the coverage maps can be contoured based on theproperties of the antennas connected to the infrastructure radiotransceivers 58. In addition, the location coordinates in the coveragemaps can be two-dimensional, x- and y-coordinates, defining location ina horizontal plane. The location coordinates can also bethree-dimensional, x-, y- and z-coordinates. Other coordinate systemscan be used, such as spherical coordinates or cylindrical coordinates.In addition, the values of the coordinates can be either global (i.e.,longitude and latitude) or expressed relative to an arbitrarily-definedorigin. In addition, the granularity of the coordinates in the coveragemaps depends on the desired granularity of the wireless node locationestimates. Furthermore, in dual-band configurations, separate coveragemaps may be maintained for each infrastructure radio transceiver 58 forthe different frequency bands (e.g., 2.4 GHz and 5 GHz).

In one implementation, the wireless node location module 59 includesmore than one RF physical model of the environment (in oneimplementation, each RF physical model is a set of coverage mapscorresponding to the antennas of the infrastructure radio transceivers58), and uses signals transmitted between the infrastructure radiotransceivers 58 to dynamically select one of the RF physical models(such as a set of coverage maps) that best characterizes the current RFenvironment. As discussed above, the propagation of RF signals iseffected by a variety of objects, including people, that move within anRF environment. In one implementation, the wireless node locationfunctionality can compare the signal strength data in the N×N IRT signalstrength matrix and the known locations of the infrastructure radiotransceivers against the RF physical models to find the best fit. In oneimplementation, infrastructure radio transceivers 58 can be configuredto transmit wireless frames at regular intervals on one to a pluralityof operating channels within a given frequency band to allow for theother infrastructure radio transceivers 58 to detect the signals. U.S.application Ser. No. 10/447,735 discloses the transmission of frames fordetection by neighboring WLAN transceivers. In another implementation,infrastructure radio transceivers 58 transmit frames, on demand, inresponse to a command issued by wireless node location module 59.

FIG. 2 illustrates a method, according to one implementation of thepresent invention, directed to estimating the location of a wirelessnode. The wireless node location functionality can be triggered ondemand, for example, in response to a command issued by a networkadministrator using a control interface to locate a mobile stationidentified by a MAC address or other suitable identifier, such as anarbitrary name associated with a MAC address in a table or other datastructure. Wireless node location module 59 may also be triggeredautomatically in response to the detection of a rogue access point. U.S.application Ser. No. 10/407,370, incorporated by reference above,discloses detection of rogue access points in a wireless network system.Wireless node location module 59 can also be configured to periodicallydetermine the location of a given mobile station in order to track itsmovement over a period of time.

A.3. Differential Signal Strength Metric

As FIG. 2 illustrates, wireless node location module 59, in oneimplementation, begins by selecting the infrastructure radiotransceivers (IRTs) 58 whose signal measurements will be used inlocating the desired wireless node (102). In one implementation,wireless node location module 59 scans the data structures discussedabove to identify the infrastructure radio transceivers 58 that see ordetect wireless frames transmitted by the desired wireless node. Inimplementations where signal strength data is regularly collected (asopposed to on demand), the time stamps in the data structures can beused to filter out infrastructure radio transceivers 58 that have notdetected the desired wireless node within a threshold period of time.Additional or alternative filter criteria can include a threshold signalstrength level (such as −80 dBm). In the implementation shown, wirelessnode location module 59 selects the M infrastructure radio transceivers58 that report the strongest signal strengths (where M is a configurableparameter). In one implementation, if an insufficient number ofinfrastructure radio transceivers 58 are identified, wireless nodelocation module 59 can command the infrastructure radio transceivers 58to actively scan for the desired wireless node and return signalstrength information. Wireless node location module 59 collects thesignal strength (e.g., RSSI) measurements corresponding to the selectedinfrastructure radio transceivers 58 (104), and identifies the RFcoverage maps to be used in estimating the location of the wireless nodebased on selected infrastructure radio transceivers 58 (106).

As FIG. 2 illustrates, wireless node location module 59, computes thedifference, ΔSS_(ij), for each pair of signal strength measurements(SS_(i) and SS_(j)) among the selected infrastructure radio transceivers58 (112), as well as the difference, ΔMAP_(ij), between the coveragemaps (MAP_(i) and MAP_(j)) corresponding to the selected infrastructureradio transceivers 58 (114). In the case of M selected infrastructureradio transceivers 58, there are N choose 2 or N!/((N−2)!2!) pairs ofdifferences. As FIG. 2 shows, wireless node location module 59constructs a total difference error surface, ErrSurfDiff, by computing,for each unique pair of infrastructure radio transceivers 58 (see 108,110), the square of the difference between ΔSS_(ij) and ΔMAP_(ij), andadding the contribution from each unique pair to ErrSurfDiff (116). Toestimate the location of the desired wireless node, wireless nodelocation module 59 selects the location that minimizes the totaldifference error surface, ErrSurfDiff (120). In one implementation,wireless node location module 59 computes the estimated location byfinding the location that minimizes the Euclidian distance in signalspace of the ErrSurfDiff, which essentially minimizes the Euclidiandistance in signal space between the detected signal strength valuedifferences and the signal strength value differences between thecorresponding coverage maps.

As the foregoing illustrates, wireless node location module 59essentially searches for the area between each pair of infrastructureradio transceivers 58 where the detected signal strength is different byX dB, where X dB is the difference in the RSSI or other signal strengthmeasurements of the desired wireless node as detected by the twoinfrastructure radio transceivers. In the ideal case involving nophysical barriers are located in the RF environment, the contour wherethe difference between the two infrastructure radio transceivers 58predicted signals is a constant X dB can be described by a Cartesianoval. In the practical world, this shape is arbitrary. In the idealworld, summing up several of these create a region of zero error wherethe Cartesian ovals overlap and non-zero error terms elsewhere. In thereal world, the summing up of several of these surfaces creates a totalerror surface, whose minimums represent the most likely location of thewireless node.

To illustrate the benefits of this differential signal strength metric,assume a N dB difference in the transmit power of the wireless node froman assumed or default transmit power. In the case of three selectedinfrastructure radio transceivers, this N dB difference factors into thetotal difference error surface as:ErrSurfDiffTxErr=(((RSSIap1+N)−(RSSIap2+N))−(MAPap1−MAPap2))^2+(((RSSIap1+N)−(RSSIap3+N))−(MAPap1−MAPap3))^2+(((RSSIap2+N)−(RSSIap3+N))−(MAPap2−MAPap3))^2,which reduces to the original ErrSurfDiff with no additional errorsadded. In addition, the differential signal strength metric alsoaddresses the errors in detecting the strength of wireless signals anderrors resulting from assuming path loss symmetry. For example, theabsolute power assumed by the coverage maps (e.g., MAPap1, MAPap2) maybe incorrect by K dB for each client independently. In this metric,those errors are also removed, as shown in the following:ErrSurfDiffAPErr=((RSSIap1−RSSIap2)−((MAPap1+K)−(MAPap2+K)))^2+((RSSIap1−RSSIap3)−((MAPap1+K)−(MAPap3+K)))^2+((RSSIap2−RSSIap3)−((MAPap2+K)−(MAPap3+K)))^2,which also reduces to ErrSurfDiff. Accordingly, the differential signalstrength metric described herein minimizes the effects of absolute errorcaused by variations in transmit power, or signal strength detection, aswell as lack of symmetry in path loss between a detecting node and atransmitting node.

A.4. Combined Use of Absolute and Differential Signal Strength Metrics

Computationally, the differential signal strength metric described aboveresults in the loss of some information, creating a greater range oflocations that may satisfy a given sample set of signal strength values.In other words, use of the differential signal strength metric, in somecircumstances and implementations, may result in several, substantiallyequal minima in the differential error surface discussed above scatteredthroughout the RF environment. In one implementation, the presentinvention uses the absolute signal strength values to optimize thelocation estimate. U.S. patent application Ser. Nos. 10/848,276 and10/802,366, incorporated by reference herein, disclose the use ofabsolute signal strength values and coverage maps to compute a totalerror surface and the selection of a location in the error surface toestimate the location of a wireless node. For example, the estimatedlocation using the absolute signal strength values can be used asguidance in selecting from the substantially equal estimated locationsthat resulted from the differential metric discussed above.

FIG. 5 illustrates a process that incorporates use of the absolutesignal strength values in connection with the differential signalstrength metric according to one implementation of the presentinvention. As FIG. 5 illustrates, wireless node location module 59computes the differential error surface (208), after collecting thesignal strength samples from selected infrastructure radio transceivers58 and selecting the corresponding coverage maps (102, 104, 106), asdiscussed above. Wireless node location module 59, in oneimplementation, also computes an error surface based on the absolutesignal strength values detected by the infrastructure radio transceivers58 (210). On the implementation shown, the error surface and thedifferential error surface are added together to essentially overlay theinformation provided by use of the absolute signal strength values tothe differential signal strength computations (212). Wireless nodelocation module 59 then estimates the location of the wireless nodebased on the aggregated error surface. In one implementation, theestimated location is the location that minimizes the aggregated error.

A variety of implementations are possible. For example, thecontributions of the differential error surface and the absolute errorsurface can be weighted. The weighting can be based on a heuristicevaluation of the RF environment in which the location system operates,and may further include analysis of factors such as whether the wirelessnode (e.g., an RFID tag) is contained within an object such as acontainer. For example, in one implementation, if the location system ofthe present invention were used to locate RFID tags located withinphysical containers, the contribution of the absolute error surfacewould typically receive a lower weighting value.

The absolute error surface can be used in other ways relative to thedifferential signal strength metric. For example, the location estimateresulting from the use of the absolute error surface can be used toselect between a plurality of equally plausible minima corresponding tothe differential error surface (e.g., where the possible locations arewithin a threshold range of being the likely location). In oneimplementation, wireless node location module 59 can be configured toselect the location from the likely locations in the differential errorsurface that is closest to the most likely location that was computedusing the absolute error surface.

B. Integration into Wireless Network Systems

In one implementation, the wireless node location functionalitydiscussed above can be integrated into a wireless networkinfrastructure, such as the hierarchical WLAN system illustrated in FIG.3. For example, the wireless node location functionality describedherein may be integrated into a WLAN environment as disclosed in U.S.application Ser. Nos. 10/155,938 and 10/407,357 incorporated byreference herein. The wireless node location functionality according tothe present invention, however, may be applied to other wireless networkarchitectures. For example, the wireless node location functionality maybe integrated into a wireless network infrastructure including aplurality of substantially autonomous access points that operate inconnection with a central network management system.

Referring to FIG. 3, there is shown a block diagram of a wireless LocalArea Network system according to an embodiment of the invention. Aspecific embodiment of the invention includes the following elements:access elements 11-15 for wireless communication with selected clientremote elements 16, 18, 20, 22, central control elements 24, 25, 26, andmeans for communication between the access elements and the centralcontrol elements, such as direct line access, an Ethernet network, suchas LAN segment 10. As disclosed in U.S. patent application Ser. No.10/407,357, the access elements, such as access elements 11-15 aredirectly connected to LAN segment 10 or a virtual local area network(VLAN) for communication with a corresponding central control element24, 26. See FIG. 3. As disclosed in U.S. patent application Ser. No.10/155,938, however, access elements 11-15 may also be directlyconnected to respective central control elements 24, 26 via directaccess lines.

The access elements 11-15 are coupled via communication means using awireless local area network (WLAN) protocol (e.g., IEEE 802.11a or802.11b, etc.) to the client remote elements 16, 18, 20, 22. Asdescribed in U.S. application Ser. Nos. 10/155,938 and 10/407,357, theaccess elements 12, 14 and the central control element 24 tunnel networktraffic associated with corresponding remote client elements 16, 18; 20,22 via direct access lines or a LAN segment 10. Central control elements24, 26 are also operative to bridge the network traffic between theremote client elements 16, 18; 20, 22 transmitted through the tunnelwith corresponding access elements 11-15. In another implementation,access elements 11-15 may be configured to bridge the network traffic onLAN segments 10, while sending copies of the bridged frames to theaccess elements for data gathering and network management purposes.

As described in the above-identified patent applications, centralcontrol elements 24, 26 operate to perform data link layer managementfunctions, such as authentication and association on behalf of accesselements 11-15. For example, the central control elements 24, 26 provideprocessing to dynamically configure a wireless Local Area Network of asystem according to the invention while the access elements 11-15provide the acknowledgment of communications with the client remoteelements 16, 18, 20, 22. The central control elements 24, 26 may forexample process the wireless LAN management messages passed on from theclient remote elements 16, 18; 20, 22 via the access elements 11-15,such as authentication requests and authorization requests, whereas theaccess elements 11-15 provide immediate acknowledgment of thecommunication of those messages without conventional processing thereof.Similarly, the central control elements 24, 26 may for example processphysical layer information. Still further, the central control elements24, 26, as discussed more fully below, may for example processinformation collected at the access elements 11-15 on channelcharacteristics, signal strength, propagation, and interference ornoise.

Central control elements 24, 26, as shown in FIG. 4, may be configuredto gather the signal strength data discussed above to support thewireless node location functionality according to the present invention.The signal strength data gathering functionality described herein isquite similar to the data gathering disclosed in U.S. application Ser.No. 10/183,704, incorporated by reference above. In that application,access elements 11-15 append signal strength data to packets receivedfrom wireless nodes, typically, in encapsulating headers. The centralcontrol elements 24, 26 process the encapsulating packet headers toupdate various data structures, such as the N×N AP signal strengthmatrix and wireless node tables discussed above in Section A. U.S.application Ser. No. 10/183,704 discloses the internal operatingcomponents and general configuration of access elements 11-15 that canbe used in connection with the integrated wireless node locationfunctionality described herein.

FIG. 4 illustrates the logical configuration of central control elements24, 26, according to an implementation of the present invention. Asdiscussed in U.S. application Ser. No. 10/183,704, in oneimplementation, there is both a logical data path 66 and a control path68 between a central control element 24 or 26 and an access element(e.g., access element 11). The control path 68 allows the centralcontrol element 24 or 26 to communicate with the radio access elements11-15 and acquire the signal strength between the radio access elements.By monitoring the data path 66, the central control element 24, 26 canobtain the signal strength of the signals transmitted by other wirelessnodes.

More specifically, the wireless node locator 90 in the central controlelement 24 or 26 collects information from a plurality of accesselements via a control channel 68 and a data channel 66. The centralcontrol element 24 or 26 receives and transmits data packets and controlpackets from/to a plurality of access elements 11-15 as described above.A flag detector 62 distinguishes between data packets and controlpackets, routing them through a logical switch 64 to a high-speed datapath 66 in communication with the wired network 15 or to control path 68within the central control element 24 or 26. The data path 66 ismonitored by a wireless node data collector 70. Associated with eachdata packet is a resource management header which contains RF physicallayer information, such as the power in the channel before each receivedpacket, an identifier for the access element receiving the signal, aswell as an identifier for the antenna selected to receive the signal.This information, together with the 802.11 protocol information in thenative frames, can be used to maintain one or more data structures thatmaintain signal strength data for the wireless nodes detected by theaccess elements 11-15, as discussed in section A, above. The controlpath 68 is coupled to a processor element 76 in which an AP signalstrength matrix 78 is maintained. The AP signal strength matrix 78collects information quantifying the signal strength between accesselements 11-15. All of the signal strength data are collected at theaccess elements 11-15 and communicated over the data path and controlpath to the central control element 24 or 26, in one implementation, aspacketized information in the resource management header in the datapath and resource management control packets in the control path,respectively.

As discussed above, in one implementation, the wireless node locationfunction uses signal strength data between access elements to select aRF physical model that best characterizes the current RF environment. Tosupport such an implementation, one task is to create and maintain an APsignal strength matrix for all the remote access elements in the variouswireless networks which detect each other's signals. This isaccomplished, in one implementation, by having the wireless node locator90 in the central control element 24 or 26 and a Resource Manager in theaccess elements 11-15 both passively listen to surrounding accesselements and actively probe for surrounding access elements. Thewireless node locator in the central control element 24 or 26 canschedule an access element 11-15 in the wireless network to transmit adata measurement request on a specified channel and then recordresponses from surrounding access elements. The data measurement proberequest and the receiver information bandwidth can have a narrowerinformation bandwidth than the normal information bandwidth in order toallow the dynamic range of the receiver to be extended beyond its normaloperational range. This allows a radio element to “see” access elementsbeyond its normal operating range. Scheduling these measurements allowsmultiple measurements to be made with a single transmission and allowsthe detection of the transmitting signal to be recognized as a change inamplitude relative to the background noise at the scheduled time,allowing for easier detection of the measurement signal and greaterdynamic range. The resulting data can be transmitted in control packetscollected by AP signal strength matrix 78 on the control path 68.Passively, for each packet received on the data channel at the accesselement a measurement of the power in the RF channel is made immediatelybefore the received packet. This interference measurement is sent to thecentral control element via the data channel by appending a RadioResource Manager header to the data packet. Alternatively, the accesselements may be configured to flag packets received from other accesselements such that they are transmitted on the control path 68.

FIG. 4 also illustrates an RF physical model database 80 containing theone or more coverage maps associated with the access elements 11-15.When activated, the wireless node locator 90 can operate as discussedabove to compute the estimated location of a desired wireless node, andreturn the estimated location to the requesting system, such as anetwork management system or a control interface. In the WLAN systemdepicted in FIG. 3, several implementations are possible. For example,central control element 24 may be configured as a “master” centralcontrol element for purposes of wireless node location. That is, datacollected at all central control elements is ultimately transmitted(either regularly or on demand) from other central control elements(e.g., central control element 26) to the master central control element24 which computes the estimated location. Alternatively, the collecteddata can be transmitted to a network management system that performs thelocation computations discussed above. Alternatively, central controlelements 24, 26 (when deployed in separate physical spaces, such asseparate floors or buildings) may operate substantially autonomously.

The invention has been explained with reference to specific embodiments.For example, although the embodiments described above operate inconnection with 802.11 networks, the present invention can be used inconnection with any wireless network environment. In addition, althoughthe embodiments described above operate in connection with a RF physicalmodel including a plurality of coverage maps or matrixes, other datastructures can be used to store the RF physical model data. Stillfurther, although the embodiments described above compute estimatedlocation based on signal strengths detected by infrastructure accesspoints or elements, the differential signal strength metric can be usedby client wireless nodes, such as mobile stations in the RADAR system.In addition, while the location algorithms discussed above consider thesquare of the Euclidean distance between the RSSI vector and the MAPvector at a particular location, other minimization functions can beconsidered, including minimum mean squared error, minimum distance, andminimum Manhattan grid distance. Other embodiments will be evident tothose of ordinary skill in the art. It is therefore not intended thatthe invention be limited except as indicated by the appended claims.

1. A method for estimating the location of a wireless node relative to aplurality of radio receivers operative to detect the strength of radiofrequency (RF) signals, wherein a RF coverage map, corresponding to eachof the radio receivers, characterizes the signal strength values forlocations in a physical region, comprising collecting signal strengthvalues, detected at a plurality of radio receivers, corresponding tosignals transmitted by a wireless node; and determining a differentialerror surface comprising, for all unique pairs of radio receivers of theplurality of radio receivers, the sum of the squares of the differencebetween the signal strength values detected by a pair of radio receiversless the difference between the signal strength values in the RFcoverage maps associated with the pair of radio receivers; andestimating the location of the wireless node using the differentialerror surface wherein estimating the location of the wireless nodefurther comprises: computing, for each radio receiver, an individualerror surface based on the RF coverage map associated with the radioreceiver and the signal strength detected by the radio receiver;aggregating the individual error surfaces to create a total absoluteerror surface; adding the total absolute error surface and thedifferential error surface; and selecting a location based on theresults of the adding step.
 2. The method of claim 1 wherein estimatingthe location comprises finding the minimum of the differential errorsurface.
 3. The method of claim 1 further comprising detecting, at aplurality of radio transceivers, the strength of signals transmitted bya wireless node.
 4. The method of claim 1 wherein the RF coverage mapseach comprise a plurality of location coordinates associated withcorresponding signal strength values.
 5. The method of claim 4 whereinthe RF coverage maps are heuristically constructed.
 6. The method ofclaim 4 wherein the RF coverage maps are based on a mathematical model.7. The method of claim 1 wherein the signals transmitted by the wirelessnodes are formatted according to a wireless communications protocol. 8.The method of claim 7 wherein the wireless communications protocol isthe IEEE 802.11 protocol.
 9. The method of claim 1 wherein only signalstrength values above a threshold signal strength value are used tocompute the estimated location of the wireless node.
 10. The method ofclaim 1 wherein the wireless node comprises an RFID tag.
 11. The methodof claim 1 wherein estimating the location of the wireless node furthercomprises finding the locations of the minimum of the results of theadding step.
 12. An apparatus facilitating the location of a wirelessnode in an RF environment, comprising a plurality of radio receiverscomprising at least one antenna, the plurality of radio receiversoperative to detect the strength of signals transmitted by wirelessnodes and provide the detected signal strengths to a wireless nodelocation model; wherein a RF coverage map, corresponding to each of theradio receivers, characterizes the signal strength values for locationsin a physical region, and a wireless node location module operative todetermine a differential error surface comprising, for all unique pairsof radio receivers of the plurality of radio receivers, the sum of thesquares of the difference between the signal strength values detected bya pair of radio receivers less the difference between the signalstrength values in the RF coverage maps associated with the pair ofradio receivers; and estimate the location of the wireless node usingthe differential error surface wherein estimating the location of thewireless node further comprises: compute, for each radio receiver, anindividual error surface based on the RF coverage map associated withthe radio receiver and the signal strength detected by the radioreceiver; aggregate the individual error surfaces to create a totalabsolute error surface; add the total absolute error surface and thedifferential error surface; and select a location based on the resultsof the adding step.
 13. The apparatus of claim 12 wherein the wirelessnode location module is operative to find the minimum of thedifferential error surface.
 14. The apparatus of claim 12 wherein the RFcoverage maps each comprise a plurality of location coordinatesassociated with corresponding signal strength values.
 15. The apparatusof claim 14 wherein the RF coverage maps are heuristically constructed.16. The apparatus of claim 14 wherein the RF coverage maps are based ona mathematical model.
 17. The apparatus of claim 12 wherein the signalstransmitted by the wireless nodes are formatted according to a wirelesscommunications protocol.
 18. The apparatus of claim 17 wherein thewireless communications protocol is the IEEE 802.11 protocol.
 19. Awireless node location mechanism operating in association with awireless network environment comprising a plurality of radio receiversoperative to detect the signal strength of signals transmitted bywireless nodes, wherein a RF coverage map, corresponding to each of theradio receivers, includes signal strength values for locations in aphysical region, comprising: a wireless node location module operativeto receive, from at least some of the plurality of radio receivers, thedetected signal strength of RF signals transmitted by a wireless node;and determine a differential error surface comprising for all uniquepairs of radio receivers of the plurality of radio receivers, the sum ofthe squares of the difference between the signal strength valuesdetected by a pair of radio receivers less the difference between thesignal strength values in the RF coverage maps associated with the pairof radio receivers; and estimate the location of the wireless node usingthe differential error surface wherein estimating the location of thewireless node further comprises: compute, for each radio receiver, anindividual error surface based on the RF coverage map associated withthe radio receiver and the signal strength detected by the radioreceiver; aggregate the individual error surfaces to create a totalabsolute error surface; add the total absolute error surface and thedifferential error surface; and select a location based on the resultsof the adding step.
 20. The wireless node location mechanism of claim 19wherein the wireless node location module is operative to find theminimum of the differential error surface.
 21. The wireless nodelocation mechanism of claim 19 wherein the RF coverage maps eachcomprise a plurality of location coordinates associated withcorresponding signal strength values.
 22. The wireless node locationmechanism of claim 21 wherein the RF coverage maps are heuristicallyconstructed.
 23. The wireless node location mechanism of claim 21wherein the RF coverage maps are based on a mathematical model.
 24. Thewireless node location mechanism of claim 19 wherein the signalstransmitted by the wireless nodes are formatted according to a wirelesscommunications protocol.
 25. The wireless node location mechanism ofclaim 24 wherein the wireless communications protocol is the IEEE 802.11protocol.
 26. The wireless node location mechanism of claim 19 furthercomprising a plurality of radio receivers operative to detect the signalstrength of signals transmitted by wireless nodes.
 27. A wirelessnetwork system facilitating the location of a wireless node, comprisinga plurality of access elements for wireless communication with at leastone remote client element and for communication with a central controlelement; wherein a RF coverage map, corresponding to each of the accesselements, characterizes the signal strength values for locations in aphysical region, wherein the access elements are each operative toestablish and maintain, in connection with a central control element,wireless connections with remote client elements; detect the strength ofreceived signals; append a signal strength value to frames received fromwireless nodes; and transmit received frames to a central controlelement; at least one central control element for supervising the accesselements, wherein the central control element is operative to managewireless connections between the access elements and correspondingremote client elements, and store signal strength data appended toframes transmitted by the plurality of access elements in associationwith wireless node identifiers; and a wireless node location moduleoperative to determine a differential error surface comprising, for allunique pairs of radio receivers of the plurality of radio receivers, thesum of the squares of the difference between the signal strength valuesdetected by a pair of radio receivers less the difference between thesignal strength values in the RF coverage maps associated with the pairof radio receivers; and estimate the location of the wireless node usingthe differential error surface wherein estimating the location of thewireless node further comprises: compute, for each access element, anindividual error surface based on the RF coverage map associated withthe access element and the signal strength detected by the accesselement; aggregate the individual error surfaces to create a totalabsolute error surface; add the total absolute error surface and thedifferential error surface; and select a location based on the resultsof the adding step.
 28. The system of claim 27 wherein the wireless nodelocation module is further operative to find the minimum of thedifferential error surface.
 29. The system of claim 27 wherein thewireless node location module resides in a network management system.30. The system of claim 27 wherein the wireless node location moduleresides in the central control element.
 31. The system of claim 27wherein the wireless node location module maintains a signal strengthmatrix including values representing the strength of signals detectedbetween the access elements.
 32. The system of claim 27 wherein theframes are 802.11 frames.
 33. The system of claim 32 wherein thewireless node identifiers are MAC addresses.
 34. The system of claim 27wherein the RF coverage maps each comprise a plurality of locationcoordinates associated with corresponding signal strength values.